English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present an end-to-end head-pose estimation network designed to predictEuler angles through the full range head yaws from a single RGB image. Existingmethods perform well for frontal views but few target head pose from allviewpoints. This has applications in autonomous driving and retail. Our networkbuilds on multi-loss approaches with changes to loss functions and trainingstrategies adapted to wide range estimation. Additionally, we extract groundtruth labelings of anterior views from a current panoptic dataset for the firsttime. The resulting Wide Headpose Estimation Network (WHENet) is the firstfine-grained modern method applicable to the full-range of head yaws (hencewide) yet also meets or beats state-of-the-art methods for frontal head poseestimation. Our network is compact and efficient for mobile devices andapplications.

WHENet: Real-time Fine-Grained Estimation for Wide Range Head Pose